The prevalence of obesity in developed countries is increasing at an alarming rate. Obesity contributes to an increased risk of heart disease, hypertension, diabetes, and some cancers and is now considered a risk factor for cardiovascular disease. Millions of people are attempting to lose weight at any time, but the rate of success at preventing weight regain remains low.
The research community devotes a significant effort toward studying effects of energy intake and expenditure on energy balance and weight gain. A fundamental baseline for each person measures how much consumed food and associated calories are required for effective weight loss or gain. Various techniques have been used to record food intake, including keeping a personal record or using a software application on a personal computer, PDA or smartphone. These techniques, however, rely on a user to record or take pictures of every meal and the portions received, which proves unlikely in practice. Other techniques have sought to automatically monitor food intake. For example, a wearable system may listen for the sound of a person swallowing or chewing to determine the rate of food consumption or count the number of hand-to-mouth gestures (“bites”). Even these wearable systems, however, are either too imprecise (such as sound-based approaches) or require input from a user (such as the hand gesture counters). A user must turn the gesture counter on or off when consuming a meal to avoid the possibility of falsely recording consumption of food throughout the day. Furthermore, many of the eyeglass-based sensors for food intake detection require direct contact of the sensors with skin and are attached using medical adhesive (e.g. EMG or strain sensors). This limits the usability of the devices and might cause discomfort to the user. These approaches are also sensitive to the placement of the sensors that require careful placement on a specific location such as temporalis muscle.
Other embodiments have attempted to incorporate accelerometers into hardware used for monitoring food consumption. Due to the limited number of activities and lack of motion from the activities of daily living, the full potential of using accelerometers on the eyeglasses was not explored. In addition, most of the published studies relying on eyeglass sensors for detection of food intake were limited to the controlled laboratory conditions and their performance was not evaluated in unconstrained free-living environment.
Another technique attempting to record food intake relies on an optical ear canal deformation sensor which receives information from three infrared proximity sensors to measure the deformation. A three-dimensional gyroscope is used to measure the motion of the body. However, in this system, the sensor blocks the ear canal and interferes with normal hearing, and the optical sensors consume a large amount of power. These limitations prevent the implementation of a truly wearable device.
At the present time there is no accurate, inexpensive, non-intrusive way to objectively quantify energy intake in free living conditions and study behavioral patterns of food consumption.